Competency A

Apply technology informatics skills to solve specific industry data and information management problems, with a focus on usability and designing for users.

Introduction

One of the ways I define Competency A is by an informatician’s ability to identify and analyze a specific business problem and propose a technological solution to help address the problem across the enterprise. While data and information are often used interchangeably with each other, these two terms are not semantically equivalent in the context of informatics: “[d]ata is a raw and unorganized fact that is required to be processed to make it meaningful,” whereas “[i]nformation is delineate because the structured, organized, and processed data, conferred inside context, that makes it relevant and helpful to the one who desires it” (Shubhamsingh10, 2022, para. 1 & 3). Because there are differences in data and information problems a business may face it warrants different approaches when an informatician pitches, develops, and implements technological solutions. Another component that is key to this competency is having an understanding of the domain the solution is being applied to and who will be using the solutions (e.g. understanding the business environment). As stated by Raiyaanakhtar786 (2022), a business environment is comprised of “economic, social, political, or institutional” factors which include the following: totality of external forces, specific and general forces, interrelatedness of elements, dynamic nature, uncertainty, complexity, and relativity (para. 2 & 3-9). Businesses are subjected to constant change from environmental forces and must understand what is going on in the market in order to be able to adapt to survive (Raiyaanakhtar786, 2022).

Domain knowledge is highly pertinent to the success of an informatics solution, where an informaticist pitches and designs the solution with the intention to give the business a competitive advantage against its competitors or return on investment (ROI) on its data and information resources; for example, one solution that was appropriate several years ago may no longer be appropriate for the business now or solutions designed for fixing problems for one application like marketing data may not be appropriate for fixing problems with healthcare data. Activities that are associated with domain knowledge can include understanding the business case, understanding the regulatory environment the organization operates in, etc.

The last part of this competency is focused around designing technological solutions with the end user in mind. Similar to the importance of domain knowledge, as discussed earlier, it’s critical that an informaticist understands how a proposed solution will be used in its respective environment and incorporates user needs into the final design. Activities involved in understanding user needs include but are not limited to the following: posing questions around how the solution will be used (i.e. who will use it, what will it need to look like, why do they need to use it, where will they use it, how will they use it, etc.), investigating user workflows, and collaboration with end users.

Discussion

In my previous informatics classes I was introduced to different aspects of Competency A. In classes like INFM 206 and INFM 210, I learned the importance of developing technical informatics solutions for data and information management with an enterprise perspective in mind. The knowledge gained from my previous courses, like INFM 206 and 210, helped me as I produced projects that put these concepts into practice. Two courses that allowed me opportunities to demonstrate my knowledge of Competency A were INFM 201 and INFM 207. In both INFM 201 and INFM 207, I was able to work on projects which focused on developing technological solutions to organizational issues.

Evidence

The two projects I submit here as evidence of demonstrating my knowledge for Competency A include the following: a paper of a CSV and JSON Python converter script I created for INFM 201 and a paper highlighting a hypothetical Digital Asset Management (DAM) implementation plan for Stern Pinball, Inc. for INFM 207. As discussed earlier in the introduction section, Competency A is a multi-tiered competency that includes identifying a business problem, related to either data or information management practices, and developing a solution that meets both the needs of the business and the end users. Both of these projects share similarities with each other because they are aimed at solving an organizational data or information management problem that can cause inefficiencies in daily operations, albeit the goals and solutions that each one of the projects proposes are different.

In the CSV and JSON Final project for INFM 201, the goal my solution was trying to solve issues with data interoperability, specifically issues with data interoperability with two common flat file formats called CSV and JSON files. According to Tejada (2022), CSV (comma-separated values) and JSON (JavaScript Object Notation) are used frequently in industry: they “are likely the most common formats used for ingesting, exchanging, and storing unstructured or semi-structured data” (para. 1) The main differences between the two flat-file formats boils down to differences in syntax: data in a CSV file is delineated or separated with commas (or tabs or spaces) with a top header row providing names of columns for the data; whereas, JSON is more similar to an XML type of syntax where “child data [is] represented inline with its parent” (Tejada, 2022, para 2 & 4). In this project, I demonstrated Competency A by designing a solution that helps to automate the process when dealing with an organizational problem of having to perform extra work needed to manually convert CSV and JSON files that must be performed before doing data analysis. The script is written in Python and is intended to work on the user’s computer using a command line interface. Essentially the script takes CSV and JSON file data, from a single directory on the user’s computer, and integrates and maps them into a single format, with key-value pairs, in the form of in-memory objects (e.g. Python dictionaries) which can be directly interacted with in Python for data analysis.

The second piece of evidence, the INFM 207 paper highlighting a hypothetical Digital Asset Management (DAM) implementation plan for Stern Pinball, Inc., differs in its end goal from the INFM 201 paper because the focus is more geared towards solving an information management organizational problem. The organizational problem that this project aims to solve is trying to fix the way Stern stores and organizes it’s institutional knowledge that are in the form of digital rich media assets (i.e. images, videos, audio files, etc.). In this paper, I laid out the ground work for a proposed technological solution to Stern’s organizational information management problem which is improving the findability, organization, and usability of digital assets through the use of a DAM platform. Some critical aspects that I needed to consider in the design of the proposed DAM platform was the domain which Stern operates in and what users of this platform will be looking for in this solution, these considerations are aligned with the goals listed in Competency A. Some of the activities performed in this project include discussing Stern’s business objectives, what digital assets Stern is looking to incorporate into their DAM, proposals for metadata models and DAM taxonomy, analysis of DAM workflow integration, digital preservation strategy, identification of potential legal/licensing issues, and a competitive review of different DAM products based on organizational needs. Solving problems and enhancing Stern’s information management practices with the DAM helps to transform it into a metadata driven organization where information produces a return on investment (ROI).

INFM 201 CSV and JSON Final Project

INFM 207 DAM Project

Conclusion

Overall these hands-on projects that demonstrate Competency A allowed me to focus on solving some real-life data and information management problems that can negatively impact the efficiency and reputation of a business. The problems that I encountered in both of these projects; data interoperability (INFM 201) and findability, organization, and usability of information (INFM 207), are common issues that organizations face and sometimes struggle to pinpoint. When working on these projects, I gained an appreciation for being able to take a step back and understand the context that the technological solution will be applied to (e.g. domain knowledge of business and understanding user needs), when confronting a problem. I was also able to gain additional technical skills, such as practice using Python 3 and using a command line interface, as well as designing metadata models tailored to specific rich media; which can be transferred into my future career plans.

References

Raiyaanakhtar786. (2022, June 15). Features and importance of business environment. GeeksforGeeks. https://www.geeksforgeeks.org/features-and-importance-of-business-environment/

Shubhamsingh10. (2022, June 15). Difference between information and data. GeeksforGeeks. https://www.geeksforgeeks.org/difference-between-information-and-data/

Tejada, Z. (2022, July 25). Working with CSV and JSON files for data solutions. Microsoft. https://docs.microsoft.com/en-us/azure/architecture/data-guide/scenarios/csv-and-json